Umeå University, Faculty of Science and Technology

Umeå University is one of Sweden’s largest higher education institutions with over 37,000 students and about 4,700 employees. The University offers a diversity of high-quality education and world-leading research in several fields. Notably, the groundbreaking discovery of the CRISPR-Cas9 gene-editing tool, which was awarded the Nobel Prize in Chemistry, was made here. At Umeå University, everything is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture.

The ongoing societal transformation and large green investments in northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here.

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The Department of Mathematics and Mathematical Statistics conducts research in computational mathematics, discrete mathematics, mathematical modelling and analysis, and mathematical statistics. Our teaching is conducted at all levels and includes mathematics, mathematical statistics and computational science. Among our partners are international research groups, academic institutions, public organizations and companies.

The Department of Mathematics and Mathematical Statistics is, together with Umeå Center for Gender Studies, searching for a PhD student in Computational Science with focus on Mathematical Statistics – Theory and methods for data-driven decisions with applications to ambulance care with special focus on gender. The employment will start on September 1, 2023, is limited to four years of full-time studies, and is based at the Department of Mathematics and Mathematical Statistics. Last day to apply is February 13, 2023.

The Department performs research in computational science, mathematics and mathematical statistics. The department has approximately 100 employees of which about 20 are PhD students see, http://www.umu.se/en/department-of-mathematics-and-mathematical-statistics/

The Graduate School of gender studies has since 2001 co-financed PhD students at all of Umeå University’s faculties. A PhD student at the Graduate School of gender studies will take part in a unique and dynamic research environment, in which about 25 PhD students are participating in, see https://www.umu.se/en/umea-centre-for-gender-studies/doctoral-studies/the-graduate-school-of-gender-studies/

Project description and tasks
As a PhD student, you will work within an interdisciplinary project that aims to develop theories and methods for data-driven decision support with applications to the Swedish ambulance care with a special focus on gender. 

Healthcare in Sweden must by law be equal, so that care and treatment are provided on equal terms to everyone regardless of gender, age, place of residence, or sexual orientation. An organizational change may give most residents better ambulance care but may also increase differences between men and women. To optimize ambulance care, we need to define relevant cost functions that penalize unequal care. 

The healthcare has access to large data, but how can we use statistics, including machine learning techniques, to turn these data into good decisions that uses the? The research project aims to answer the following key questions:

  • Based on a set of values – how can we combine different interests when we make decisions?
  • How can we make optimal decisions?
  • What information is needed to make these decisions?
  • How can we use statistics to extract the required information from the available data?

The doctoral project aims to develop new theory for data-driven decision support, develop a data-driven decision support system for ambulance care, and to describe the ambulance care in northern Sweden based on demographic and geographical parameters with a special focus on gender. 

The main supervisor of the project is Patrik Rydén, who is running an interdisciplinary research project with the goal of optimizing ambulance care in Sweden. The project has access to unique ambulance data and established contacts with prehospital care.

Qualifications
Prerequisites include 240 ECTS credits of higher education studies of which 60 ECTS credits should be on an advanced level (Master’s level).

In addition to these general requirements, the applicant is required to have completed at least 90 ECTS credits in computational science courses, of which at least 30 credits shall have been acquired at the advanced level (Master’s level). Computational science courses refer to courses in statistics, mathematical statistics or computer science. Applicants who in some other system either within Sweden or abroad have acquired largely equivalent skills are also eligible.

Examples of relevant academic background are applied mathematics, engineering or an equivalent degree on advanced level in a related field.

We are looking for a highly motivated person with a great interest in the research area that includes theory development in mathematical statistics, gender issues and interdisciplinary applications.

Good knowledge of statistics or mathematical statistics, programming (preferably MatLab, Python or R) and English is a requirement. Good knowledge of Swedish is a merit. Knowledge of gender studies and knowledge of gender research is a merit.

You are expected to have external collaborations and should therefore be solution-oriented, flexible, structured and be good at communicating and collaborating.

The assessments of the applicants are based on their qualifications and their ability to benefit from the doctoral-level education they will receive.

Applicants with a degree not from a Swedish university are encouraged to provide results obtained from GMAT (and/or GRE) and TOEFL/IELTS tests if available.

About the employment
The position is intended to result in a doctoral degree and the main task of the PhD student is to pursue their doctoral studies which include both participation in research and postgraduate courses. The duties can include teaching and other departmental work (up to a maximum of 20%). The employment is limited to four years of full-time or up to five years for teaching part-time. Salary is set in accordance with the established salary ladder for PhD position. The employment will start on September 1, 2023.

Application
A complete application should contain the following documents:

  • a personal letter with a brief description of your qualifications and your research interests. Motivate why you are applying and describe how your qualifications and merits are relevant to the employment.
  • a curriculum vitae.
  • reinforced copies of diplomas or equivalent, including documentation of completed academic courses, grades obtained, and possibly other certificates.
  • copies of relevant work such as Master’s thesis or articles that you have authored or co-authored.
  • contact information for at least two reference persons.

The Department of Mathematics and Mathematical Statistics values an even gender distribution and encourage female applicants. You apply via our e-recruitment system Varbi. Log in and apply via the button at the bottom of the page. The deadline for applications is 2023-02-13.

The procedure for recruitment for the position is in accordance with the Higher Education Ordinance (chapter 12, 2§) and the decision regarding the position cannot be appealed.

Further information
Further information is provided by Patrik Rydén on e-mail patrik.ryden@umu.se or phone +46 90 786 9562.

We look forward to receiving your application!

Type of employment Temporary position
Contract type Full time
Salary Månadslön
Number of positions 1
Full-time equivalent 100%
City Umeå
County Västerbottens län
Country Sweden
Reference number AN 2.2.1-2055-22
Contact
  • Patrik Rydén, professor, 090-7869562,patrik.ryden@umu.se
Union representative
  • SACO, 090-7865365
  • SEKO, 090-7865296
  • ST, 090-7865431
Published 13.Jan.2023
Last application date 13.Feb.2023 11:59 PM CET

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